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ASME Press Select Proceedings
Intelligent Engineering Systems through Artificial Neural Networks, Volume 16
ISBN-10:
0791802566
No. of Pages:
1000
Publisher:
ASME Press
Publication date:
2006
eBook Chapter
87 Fault Diagnosis Using an Observers Bank of Dynamic Neural Networks
By
Thamara Villegas
,
Thamara Villegas
University of Valladolid
. Department of Systems Engineering and Control. Valladolid
, Spain
; thamara@autom.uva.es
Search for other works by this author on:
María J. Fuente
María J. Fuente
University of Valladolid
. Department of Systems Engineering and Control. Valladolid
, Spain
; maria@autom.uva.es
Search for other works by this author on:
Page Count:
6
-
Published:2006
Citation
Villegas, T, & Fuente, MJ. "Fault Diagnosis Using an Observers Bank of Dynamic Neural Networks." Intelligent Engineering Systems through Artificial Neural Networks, Volume 16. Ed. Dagli, CH, Buczak, AL, Enke, DL, Embrechts, M, & Ersoy, O. ASME Press, 2006.
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This paper describes the application of techniques based on dynamic neural networks for fault diagnosis. Two architectures of dynamic neural networks are used. The better net is integrated in a state observer bank, where each net describes one system behavior. Training in closed loop is used. The method of fault detection and diagnosis is based on the definition of minimum errors (residues). These residues are calculated by comparing the plant outputs and each dynamic neural network output from the state observer bank, with and without faults. Finally, this technique is applied to a tanks system, and can be demonstrated that...
Abstract
Introduction
Dynamic Neural Networks
Experimental System
Experiment Design
Experimental Results
Conclusions
Acknowledgment
Nomenclature
References
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